Traditional metabolic engineering has often focused on the rational design of metabolic pathways, relying on extensive a priori knowledge of cellular mechanisms in order to redirect metabolite flow, revise metabolic regulation, or introduce new pathways to achieve a particular phenotype (4). In recent years, however, considerable advances in molecular biology and the growing availability of annotated genome sequences have made combinatorial methods of metabolic engineering an increasingly attractive approach for strain improvement. With these search strategies, random, traceable genetic-level perturbations are introduced into a cell to yield a new population of strains with a diverse range of properties. A screen is then implemented in order to probe these mutant libraries for strains exhibiting enhancements in the trait of interest. The potential of the combinatorial approach has already been demonstrated for a number of genetic tools and cellular phenotypes. For example, the use of random knockout and overexpression libraries generated via transposon mutagenesis and genomic complementation respectively has led to the isolation of Escherichia coli strains with significant increases in the production of the carotenoid lycopene (1, 14). More recently, cell-wide perturbations elicited from global transcription machinery engineering (gTME) has been shown to be effective in improving the tolerance of E. coli and Saccharomyces cerevisiae to a variety of solvents, including sodium dodecyl sulfate (SDS) and ethanol (2, 3). In each of these examples, the phenotypes of interest could be easily accessed, either by visual selection of red bacterial colonies for the case of lycopene production or a simple growth competition assay for the case of solvent tolerance. For most systems of interest, however, the widespread use of these combinatorial approaches is hampered by the absence of a high-throughput method for selecting strains with the desired cellular properties.
Although L-tyrosine has received far less attention than the other aromatic amino acids, L-tryptophan and L-phenylalanine, it remains a valuable target compound for microbial production. Apart from its use as a dietary supplement, L-tyrosine also serves as a precursor for L-dihydroxyphenylalanine (L-DOPA), a Parkinson's disease drug, and thyroid hormone, used in the treatment of Basedow's or Graves' disease (6). Additionally, L-tyrosine is involved in the synthesis of p-hydroxycinnamic acid and p-hydroxystyrene, both of which serve as starting materials for a variety of novel polymers, adhesives and coatings, pharmaceuticals, biocosmetics, and health and nutrition products (20, 23).
Most prior work on the microbial production of aromatic amino acids has focused largely on two main goals: 1) alleviating the feedback regulation of the product-forming pathway, and, 2) altering central carbon metabolism in order to increase the supply of the two main precursors, erythrose-4-phosphate (E4P) and phosphoenolpyruvate (PEP). The intrinsic regulation of the pathway was disrupted through the deletion of the transcriptional regulator, TyrR, as well as the overexpression of feedback resistant forms of some of the key rate-controlling enzymes. In order to ensure an adequate supply of E4P and PEP, various groups have also tried overexpressing genes responsible for their generation (tktA, talB, pps, pck) and deleting those that deplete the supply of these precursors (ppc, pyrkA, pykF, pts) (5, 6, 13, 24). Although these approaches have certainly led to significant increases in aromatic amino acid production, further gains in yield and productivity may require the modulation of factors that are not directly involved in the biosynthetic pathway or the related precursor forming/utilization reactions. Implementation of the combinatorial metabolic engineering approaches discussed earlier would allow for the identification of these more obscure targets, which may act through unknown or poorly understood mechanisms. A high-throughput screen capable of selecting L-tyrosine-producing mutants from a large, diverse population thus becomes an important tool for the future engineering of these production strains.
For the case of tyrosine production in standard amino acid production host organisms, the current approaches used for measuring tyrosine content in cell cultures, such as High Performance Liquid Chromatography (HPLC) and 1-nitroso-2-naphthol derivatization (26, 27), possess several disadvantages as high throughput screening tools. Although the 1-nitroso-2-naphthol colorimetric/fluorimetric assay can be implemented in a 96-well plate format, the need for strongly acidic reagents and the complexity of sample preparation and derivatization make it an unattractive procedure for testing large numbers of mutants. Despite the sensitivity of HPLC measurements, its low capacity allows for the analysis of less than 100 samples per day, thereby eliminating it as a potential screening tool.